Abstract 5637: Path to the holy grail of spatial biology: Spatial single-cell whole transcriptomes using 6000-plex spatial molecular imaging on FFPE tissue
Authors: Shanshan He, Michael Patrick, Jason W. Reeves, Patrick Danaher, Julian Preciado, Joseph Phan, Erin Piazza, Zachary Reitz, Lidan Wu, Rustem Khafizov, Haiyan Zhai, Michael Rhodes, David Ruff, Joseph Beechem
Journal: Cancer Research (2023)

Abstract Cancer research across drug development, molecular biomarkers, and patient response depends on understanding biology that is dependent on complex interactions between malignant, immune, and stromal cells. To survive clearance mechanisms, a tumor can rely on a myriad of escape strategies, and the microenvironment is architected around the current path of escape. To enable a more comprehensive picture of tumor biology, we have developed the CosMx™ Spatial Molecular Imager (SMI) technology to capture a snapshot of thousands of RNA species resolved subcellularly from a single, standard histopathology slide. Building upon the previously released panels, this study tests a new 6,000-plex panel, the highest RNA plex measured in situ within human tissue, allowing the imputation of a spatial whole transcriptome in the tissue. We performed an ultra-high-plex RNA assay to detect 6,000 targets simultaneously in situ on an FFPE human liver cancer tissue (~1 cm2 area) using the CosMx SMI. This RNA panel covers broad biological areas with special emphasis on oncology, immunology, and signal transduction, such that all cancer researchers can benefit from the direct detection of targets of interest (sans imputation) in intact tissue. Analysis algorithms were developed to allow robust assessments of cell types, cell states, cell-cell interactions, and pathway activation. Imputation based on reference profiles from HCA, TCGA, and other public repositories allows estimation of non-measured transcripts at a ratio of approximately 1:3, compared to the approximate 1:20-1:70 imputations performed previously for spatial data.Thousands of transcripts were simultaneously detected with high sensitivity and specificity on the FFPE liver cancer tissue section at single-cell subcellular resolution. We were able to accurately map known reference profiles from scRNA-seq into this sample while identifying cancer-specific malignant, immune, and stromal cells in this tissue sample using this ultra-high plex RNA panel. In addition, we constructed sample-specific spatial neighborhoods, defined by cell types, cell states, and nearly unlimited sets of biological pathways through the imputed whole transcriptome. Finally, we measured &amp;gt;1,000 ligand-receptor interactions between key cell types of adjacent cells in the tissue, identifying mechanisms for tumor-mediated escape as well as reactive re-architecting of the native stroma which defines the trajectory of cancer’s evolution. Single-cell spatial measurements of gene expression at 6,000 plex from a single FFPE slide has the potential to transform our understanding of tumor biology and facilitate the next advances in cancer research by extracting the highest data density possible from rare specimens collected during patient treatment. Citation Format: Shanshan He, Michael Patrick, Jason W. Reeves, Patrick Danaher, Julian Preciado, Joseph Phan, Erin Piazza, Zachary Reitz, Lidan Wu, Rustem Khafizov, Haiyan Zhai, Michael Rhodes, David Ruff, Joseph Beechem. Path to the holy grail of spatial biology: Spatial single-cell whole transcriptomes using 6000-plex spatial molecular imaging on FFPE tissue. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5637.